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Changes in the interaction of resting-state neural networks from adolescence to adulthood

Authors

  • Michael C. Stevens,

    Corresponding author
    1. Olin Neuropsychiatry Research Center, 200 Retreat Avenue, Hartford, Connecticut
    2. Department of Psychiatry, Yale University School of Medicine, 34 Park Street, New Haven, Connecticut
    • Olin Neuropsychiatry Research Center, Whitehall Building, The Institute of Living/Hartford Hospital, Hartford, Connecticut 06106
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  • Godfrey D. Pearlson,

    1. Olin Neuropsychiatry Research Center, 200 Retreat Avenue, Hartford, Connecticut
    2. Department of Psychiatry, Yale University School of Medicine, 34 Park Street, New Haven, Connecticut
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  • Vince D. Calhoun

    1. Olin Neuropsychiatry Research Center, 200 Retreat Avenue, Hartford, Connecticut
    2. Department of Psychiatry, Yale University School of Medicine, 34 Park Street, New Haven, Connecticut
    3. The Mind Research Network, 1101 Yale Boulevard, Albuquerque, New Mexico
    4. Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, New Mexico
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Abstract

This study examined how the mutual interactions of functionally integrated neural networks during resting-state fMRI differed between adolescence and adulthood. Independent component analysis (ICA) was used to identify functionally connected neural networks in 100 healthy participants aged 12–30 years. Hemodynamic timecourses that represented integrated neural network activity were analyzed with tools that quantified system “causal density” estimates, which indexed the proportion of significant Granger causality relationships among system nodes. Mutual influences among networks decreased with age, likely reflecting stronger within-network connectivity and more efficient between-network influences with greater development. Supplemental tests showed that this normative age-related reduction in causal density was accompanied by fewer significant connections to and from each network, regional increases in the strength of functional integration within networks, and age-related reductions in the strength of numerous specific system interactions. The latter included paths between lateral prefrontal-parietal circuits and “default mode” networks. These results contribute to an emerging understanding that activity in widely distributed networks thought to underlie complex cognition influences activity in other networks. Hum Brain Mapp 2009. © 2009 Wiley-Liss, Inc.

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